
This selfStart
model evaluates the logistic
function and its gradient. It has an initial
attribute that
creates initial estimates of the parameters Asym
,
xmid
, and scal
. In R 3.4.2 and earlier, that
init function failed when min(input)
was exactly zero.
SSlogis(input, Asym, xmid, scal)
a numeric vector of values at which to evaluate the model.
a numeric parameter representing the asymptote.
a numeric parameter representing the x
value at the
inflection point of the curve. The value of SSlogis
will be
Asym/2
at xmid
.
a numeric scale parameter on the input
axis.
a numeric vector of the same length as input
. It is the value of
the expression Asym/(1+exp((xmid-input)/scal))
. If all of
the arguments Asym
, xmid
, and scal
are
names of objects the gradient matrix with respect to these names is attached as
an attribute named gradient
.
# NOT RUN {
Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ]
SSlogis(Chick.1$Time, 368, 14, 6) # response only
Asym <- 368; xmid <- 14; scal <- 6
SSlogis(Chick.1$Time, Asym, xmid, scal) # response and gradient
getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
## Initial values are in fact the converged values
fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
summary(fm1)
# }
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